The properties of some covariance matrix estimators in linear models with AR(1) errors

Abstract

A Monte Carlo study is used to demonstrate how poor some traditional covariance matrix estimators can be in linear models with AR(1) errors. It is also shown that a second-order approximation suggested recently by Ullah et al. (1983) does not lead to a more accurate covariance matrix estimator. © 1984.